Psycho-sociological research has historically shown a lack of representation towards Low- and Middle Income Countries (LMIC), yet the issues faced by these countries, especially in the domains of child development and public health, are much more severe and prevalent. To close this research gap, the Multiple Indicator Cluster Survey (MICS) is an appropriate and comprehensive large dataset that captures information on LMIC health and human development. We therefore introduce mics_library, a tool designed to help researchers using the MICS dataset by allowing data preview, organizing files and extracting relevant data. © 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

mics-library: A Python package for reproducible studies on the Multiple Indicator Cluster Survey / Bizzego, Andrea; Lim, Mengyu; Esposito, Gianluca. - In: SOFTWAREX. - ISSN 2352-7110. - 16:(2021), pp. 100828.1-100828.6. [10.1016/j.softx.2021.100828]

mics-library: A Python package for reproducible studies on the Multiple Indicator Cluster Survey

Bizzego, Andrea;Esposito, Gianluca
2021-01-01

Abstract

Psycho-sociological research has historically shown a lack of representation towards Low- and Middle Income Countries (LMIC), yet the issues faced by these countries, especially in the domains of child development and public health, are much more severe and prevalent. To close this research gap, the Multiple Indicator Cluster Survey (MICS) is an appropriate and comprehensive large dataset that captures information on LMIC health and human development. We therefore introduce mics_library, a tool designed to help researchers using the MICS dataset by allowing data preview, organizing files and extracting relevant data. © 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
2021
Bizzego, Andrea; Lim, Mengyu; Esposito, Gianluca
mics-library: A Python package for reproducible studies on the Multiple Indicator Cluster Survey / Bizzego, Andrea; Lim, Mengyu; Esposito, Gianluca. - In: SOFTWAREX. - ISSN 2352-7110. - 16:(2021), pp. 100828.1-100828.6. [10.1016/j.softx.2021.100828]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/329771
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